Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

doi:10.1038/nm.3933

Meta-Analysis

. 2015 Sep;21(9):1018-27.

doi: 10.1038/nm.3933. Epub 2015 Aug 24.

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Yun R Li^{1

2}, Jin Li¹, Sihai D Zhao³, Jonathan P Bradfield¹, Frank D Mentch¹, S Melkorka Maggadottir^{1

4}, Cuiping Hou¹, Debra J Abrams¹, Diana Chang^{5

6}, Feng Gao⁵, Yiran Guo¹, Zhi Wei⁷, John J Connolly¹, Christopher J Cardinale¹, Marina Bakay¹, Joseph T Glessner¹, Dong Li¹, Charlly Kao¹, Kelly A Thomas¹, Haijun Qiu¹, Rosetta M Chiavacci¹, Cecilia E Kim¹, Fengxiang Wang¹, James Snyder¹, Marylyn D Richie⁸, Berit Flatø⁹, Øystein Førre⁹, Lee A Denson¹⁰, Susan D Thompson¹¹, Mara L Becker¹², Stephen L Guthery¹³, Anna Latiano¹⁴, Elena Perez¹⁵, Elena Resnick¹⁶, Richard K Russell¹⁷, David C Wilson¹⁸, Mark S Silverberg¹⁹, Vito Annese²⁰, Benedicte A Lie²¹, Marilynn Punaro²², Marla C Dubinsky²³, Dimitri S Monos^{24

25}, Caterina Strisciuglio²⁶, Annamaria Staiano²⁶, Erasmo Miele²⁶, Subra Kugathasan²⁷, Justine A Ellis^{28

29}, Jane E Munro^{30

31}, Kathleen E Sullivan^{4

25}, Carol A Wise³², Helen Chapel³³, Charlotte Cunningham-Rundles¹⁶, Struan F A Grant^{1

25}, Jordan S Orange³⁴, Patrick M A Sleiman^{1

25}, Edward M Behrens^{25

35}, Anne M Griffiths³⁶, Jack Satsangi³⁷, Terri H Finkel³⁸, Alon Keinan^{5

6}, Eline T Luning Prak³⁹, Constantin Polychronakos⁴⁰, Robert N Baldassano^{25

41}, Hongzhe Li³⁹, Brendan J Keating^{1

25}, Hakon Hakonarson^{1

25

42}

Affiliations

¹ The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
² Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
³ Department of Biostatistics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁴ Division of Allergy and Immunology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁵ Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.
⁶ Program in Computational Biology and Medicine, Cornell University, Ithaca, New York, USA.
⁷ Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA.
⁸ Department of Biochemistry and Molecular Biology, Eberly College of Science, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, USA.
⁹ Department of Rheumatology, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
¹⁰ Division of Gastroenterology, The Center for Inflammatory Bowel Disease, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
¹¹ Divison of Rheumatology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
¹² Division of Rheumatology, Children's Mercy Hospitals and Clinics, Kansas City, Missouri, USA.
¹³ Department of Pediatrics, University of Utah School of Medicine and Primary Children's Medical Center, Salt Lake City, Utah, USA.
¹⁴ Division of Gastroenterology, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
¹⁵ Division of Pediatric Allergy and Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA.
¹⁶ Institute of Immunology and Department of Medicine, Mount Sinai School of Medicine, New York, New York, USA.
¹⁷ Department of Paediatric Gastroenterology, Yorkhill Hospital for Sick Children, Glasgow, Scotland, UK.
¹⁸ Paediatric Gastroenterology and Nutrition, Royal Hospital for Sick Children, University of Edinburgh, Ediburgh, UK.
¹⁹ Mount Sinai Hospital IBD Centre, University of Toronto, Toronto, Ontario, Canada.
²⁰ Unit of Gastroenterology, Department of Medical and Surgical Specialties, Careggi University Hospital, Florence, Italy.
²¹ Department of Immunology, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
²² Department of Rheumatology, Texas Scottish Rite Hospital for Children, Dallas, Texas, USA.
²³ Department of Pediatrics, Pediatric IBD Center, Cedars Sinai Medical Center, Los Angeles, California, USA.
²⁴ Department of Pathology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
²⁵ Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
²⁶ Department of Translational Medical Science, Section of Pediatrics, University of Naples Federico II, Naples, Italy.
²⁷ Department of Pediatrics, Emory University School of Medicine and Children's Health Care of Atlanta, Atlanta, Georgia, USA.
²⁸ Genes, Environment and Complex Disease, Murdoch Children's Research Institute, Parkville, Victoria, Australia.
²⁹ Department of Pediatrics, University of Melbourne, Parkville, Victoria, Australia.
³⁰ Pediatric Rheumatology Unit, Royal Children's Hospital, Parkville, Victoria, Australia.
³¹ Arthritis and Rheumatology Research, Murdoch Children's Research Institute, Parkville, Victoria, Australia.
³² Sarah M. and Charles E. Seay Center for Musculoskeletal Research, Texas Scottish Rite Hospital for Children, Dallas, Texas, USA.
³³ Department of Clinical Immunology, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
³⁴ Section of Immunology, Allergy, and Rheumatology, Department of Pediatric Medicine, Texas Children's Hospital, Houston, Texas, USA.
³⁵ Division of Rheumatology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
³⁶ The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
³⁷ Gastrointestinal Unit, Division of Medical Sciences, School of Molecular and Clinical Medicine, University of Edinburgh, Edinburgh, UK.
³⁸ Department of Pediatrics, Nemours Children's Hospital, Orlando, Florida, USA.
³⁹ Department of Pathology and Lab Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁴⁰ Departments of Pediatrics and Human Genetics, McGill University Health Centre Research Institute, Montréal, Québec, Canada.
⁴¹ Division of Gastroenterology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁴² Division of Pulmonary Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

PMID: 26301688
PMCID: PMC4863040
DOI: 10.1038/nm.3933

Meta-Analysis

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Yun R Li et al. Nat Med. 2015 Sep.

. 2015 Sep;21(9):1018-27.

doi: 10.1038/nm.3933. Epub 2015 Aug 24.

Authors

Affiliations

¹ The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
² Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
³ Department of Biostatistics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁴ Division of Allergy and Immunology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁵ Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.
⁶ Program in Computational Biology and Medicine, Cornell University, Ithaca, New York, USA.
⁷ Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA.
⁸ Department of Biochemistry and Molecular Biology, Eberly College of Science, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, USA.
⁹ Department of Rheumatology, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
¹⁰ Division of Gastroenterology, The Center for Inflammatory Bowel Disease, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
¹¹ Divison of Rheumatology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
¹² Division of Rheumatology, Children's Mercy Hospitals and Clinics, Kansas City, Missouri, USA.
¹³ Department of Pediatrics, University of Utah School of Medicine and Primary Children's Medical Center, Salt Lake City, Utah, USA.
¹⁴ Division of Gastroenterology, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy.
¹⁵ Division of Pediatric Allergy and Immunology, University of Miami Miller School of Medicine, Miami, Florida, USA.
¹⁶ Institute of Immunology and Department of Medicine, Mount Sinai School of Medicine, New York, New York, USA.
¹⁷ Department of Paediatric Gastroenterology, Yorkhill Hospital for Sick Children, Glasgow, Scotland, UK.
¹⁸ Paediatric Gastroenterology and Nutrition, Royal Hospital for Sick Children, University of Edinburgh, Ediburgh, UK.
¹⁹ Mount Sinai Hospital IBD Centre, University of Toronto, Toronto, Ontario, Canada.
²⁰ Unit of Gastroenterology, Department of Medical and Surgical Specialties, Careggi University Hospital, Florence, Italy.
²¹ Department of Immunology, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
²² Department of Rheumatology, Texas Scottish Rite Hospital for Children, Dallas, Texas, USA.
²³ Department of Pediatrics, Pediatric IBD Center, Cedars Sinai Medical Center, Los Angeles, California, USA.
²⁴ Department of Pathology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
²⁵ Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
²⁶ Department of Translational Medical Science, Section of Pediatrics, University of Naples Federico II, Naples, Italy.
²⁷ Department of Pediatrics, Emory University School of Medicine and Children's Health Care of Atlanta, Atlanta, Georgia, USA.
²⁸ Genes, Environment and Complex Disease, Murdoch Children's Research Institute, Parkville, Victoria, Australia.
²⁹ Department of Pediatrics, University of Melbourne, Parkville, Victoria, Australia.
³⁰ Pediatric Rheumatology Unit, Royal Children's Hospital, Parkville, Victoria, Australia.
³¹ Arthritis and Rheumatology Research, Murdoch Children's Research Institute, Parkville, Victoria, Australia.
³² Sarah M. and Charles E. Seay Center for Musculoskeletal Research, Texas Scottish Rite Hospital for Children, Dallas, Texas, USA.
³³ Department of Clinical Immunology, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
³⁴ Section of Immunology, Allergy, and Rheumatology, Department of Pediatric Medicine, Texas Children's Hospital, Houston, Texas, USA.
³⁵ Division of Rheumatology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
³⁶ The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
³⁷ Gastrointestinal Unit, Division of Medical Sciences, School of Molecular and Clinical Medicine, University of Edinburgh, Edinburgh, UK.
³⁸ Department of Pediatrics, Nemours Children's Hospital, Orlando, Florida, USA.
³⁹ Department of Pathology and Lab Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
⁴⁰ Departments of Pediatrics and Human Genetics, McGill University Health Centre Research Institute, Montréal, Québec, Canada.
⁴¹ Division of Gastroenterology, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁴² Division of Pulmonary Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

PMID: 26301688
PMCID: PMC4863040
DOI: 10.1038/nm.3933

Abstract

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases.

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Figures

**Figure 1**
The ten pAID case cohorts and top pAID-association loci identified. (a) Percentage and relative contribution of cases for the ten pediatric autoimmune diseases studied. (b) Top pAID-association signals identified by inverse χ² meta-analysis. The top 27 loci (where at least one lead SNP reached genome-wide significance: P_META < 5 × 10⁻⁸) are annotated with the candidate gene symbol. (c) Novel and established pAID-association loci. Top left: rs706778 (chr10p15.1) is a known DNase I peak and an intronic SNP in *IL2RA* and was associated with THY, AS, PSOR, CEL, T1D and JIA. Top right: rs755374 (chr5q33.3) is an intergenic SNP upstream of *IL12B* and was associated with AS, CEL, UC and CD. Bottom left: rs2807264 (chrXq26.3), mapping near *CD40LG*, was associated with CEL, UC and CD, and chr15q22.33 (rs72743477), also mapping to an intronic position in *SMAD3*, was associated with UC, CD and AS. Bottom right: SNPs are colored according to pairwise LD (r²) with respect to the most strongly associated lead SNP in the locus. Associated pAIDs are indicated at the upper left. pAID associations are color-coded according to the key in each plot. (d) Pleiotropic candidate genes have pleiotropic effect sizes and directions across pAIDs. Although a few pleiotropic SNPs had consistent effect directions across diseases (e.g., *IL21*), for many loci (e.g., *PTPN22* and *CLEC16A*), the candidate SNP had variable effect directions across diseases. The radii of the wedges correspond to the absolute values of the Z-scores (beta/s.e.) for each pAID, and the color indicates whether the SNP is protective (green) or risk-associated (red) for each disease.

**Figure 2**
Pleiotropic loci with heterogeneous effect directions across pAIDs. (a) Disease-specific Z-scores (beta/s.e.) for each SNP identified as having different effect directions across the ten pAIDs and as detailed in the figure. Circles (color-coded by disease as in key) denote diseases where the indicated SNP had an opposite effect compared with that of the group of pAIDs identified as sharing the lead association on the basis of results of the model search (black triangles). (b) Clustering of pAIDs across the lead loci on the basis of disease-specific effect sizes. Agglomerative hierarchical clustering across ten pAIDs on the basis of normalized directional Z-scores (beta/s.e.) resulting from logistic regression analysis in each disease for the 27 lead loci based on those disease combinations identified by the model search analysis as producing the strongest association-test statistics.

**Figure 3**
Integrated annotation of pAID-association loci using existing predictive and experimental data sets. (a) Biological, functional and literature annotations for the 27 loci reaching genome-wide significance in meta-analysis. Loci (identified by the lead SNPs and candidate genes) are organized by column; the colors in the table denote the associated pAIDs, functional annotations are presented at the top of the table, and the color bar at the bottom represents the meta-analysis P_meta values (according to key at right). For each locus, the lead SNP and proxy SNPs (r² > 0.8) were included in the annotation protocol (Online Methods). (b) Distribution and enrichment of experimental and predicted annotations for the top 27 GWS SNPs. The annotation frequencies were used to calculate the relative enrichment of pAID SNPs (blue bars) as compared with that of 10,000 random 100-SNP sets drawn from the genome in each annotation category. CpG, CpG islands; DNase, DNase-hypersensitivity I sites; gad, known genetic association; gerp_phast, conserved positions; mir, miRNAs; sift_pp, functional mutations in SIFT; tfbs, TF–binding sites.

**Figure 4**
Tissue-specific gene set enrichment analysis (TGSEA) of pediatric and adult autoimmune data sets identifies autoimmune-associated gene expression patterns across immune cells and tissues. (a) Expression enrichment of autoimmune-associated genes across human tissues. Distribution of TGSEA enrichment score (ES) values across 126 tissues for pAID-associated genes (center) either with (circles, top curve) or without (triangles, bottom curve) the extended MHC. Results for the pAID gene set are compared with those obtained for known genes associated with CD (left) and schizophrenia (right). Tissue and cell types are classified as immune (red) or non-immune (blue) and are ranked left to right on the basis of the magnitude of the ES test statistic. (b) Enrichment of pAID-associated gene expression across diverse murine immune cell types. Distribution of pAID-associated gene ES values across murine immune cell types either including (red) or excluding the genes within the MHC (gold); results are compared with those for genes associated with CD, schizophrenia (Schizo, turquoise), LDL cholesterol (LDL, magenta) or body mass index (BMI, blue) abstracted from the National Human Genome Research Institute (NHGRI) GWAS Catalog. (c) Hierarchical clustering based on the expression of pleiotropic candidate genes associated with three or more autoimmune diseases across the murine immune cells. Boxes outlined in black denote gene clusters enriched for specific disease associations discussed in the text. An enlarged version of c is presented in Supplementary Figure 8.

**Figure 5**
Genetic variants shared across the ten pAIDs reveal autoimmune disease networks. (a) Quantification of pAID genetic sharing by GPS test including SNPs within the extended MHC. Correlation plot of results of the pairwise pAID GPS test; the color intensity and the size of each circle are proportional to the strength of the correlation as the negative base ten logarithms of the GPS test P values (color-coded numbers in squares). (b) Quantification of autoimmune disease genetic sharing by locus-specific pairwise sharing. Undirected weighted network graph depicting results from the LPS test. Edge size represents the magnitude of the LPS test statistic; labeled nodes for each of the 17 autoimmune diseases are positioned on the basis of a force-directed layout. Edges represent significant pairs after Bonferroni adjustment (P_adj < 0.05). (c) Protein-protein interaction network analysis of the top pAID-associated protein candidates in STRING; action view of protein interactions observed across the top 46 GWM (P < 1 × 10⁻⁶) signals, of which 44 could be mapped to corresponding proteins. Views were generated on the basis of results for known and predicted protein interactions produced by the STRING DB *Homo sapiens* database. The plots shown are results of the ‘action’ view, where the molecular actions (stimulatory, repressive or binding) are illustrated by arrows.

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Comment in

Genetics. Meta-analysis reveals novel overlap in genetic aetiologies of paediatric autoimmune disorders.
Onuora S. Onuora S. Nat Rev Rheumatol. 2015 Oct;11(10):561. doi: 10.1038/nrrheum.2015.120. Epub 2015 Sep 8. Nat Rev Rheumatol. 2015. PMID: 26345117 No abstract available.

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References

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1. Cooper JD, et al. Seven newly identified loci for autoimmune thyroid disease. Hum. Mol. Genet. 2012;21:5202–5208. - PMC - PubMed
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1. Liu JZ, et al. Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis. Nat. Genet. 2012;44:1137–1141. - PMC - PubMed

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[1] Cooper GS, Bynum ML, Somers EC. Recent insights in the epidemiology of autoimmune diseases: improved prevalence estimates and understanding of clustering of diseases. J. Autoimmun. 2009;33:197–207. - PMC - PubMed

[2] Cooper GS, Bynum ML, Somers EC. Recent insights in the epidemiology of autoimmune diseases: improved prevalence estimates and understanding of clustering of diseases. J. Autoimmun. 2009;33:197–207. - PMC - PubMed

[3] Cooper JD, et al. Seven newly identified loci for autoimmune thyroid disease. Hum. Mol. Genet. 2012;21:5202–5208. - PMC - PubMed

[4] Cooper JD, et al. Seven newly identified loci for autoimmune thyroid disease. Hum. Mol. Genet. 2012;21:5202–5208. - PMC - PubMed

[5] Tsoi LC, et al. Identification of 15 new psoriasis susceptibility loci highlights the role of innate immunity. Nat. Genet. 2012;44:1341–1348. - PMC - PubMed

[6] Tsoi LC, et al. Identification of 15 new psoriasis susceptibility loci highlights the role of innate immunity. Nat. Genet. 2012;44:1341–1348. - PMC - PubMed

[7] Hinks A, et al. Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis. Nat. Genet. 2013;45:664–669. - PMC - PubMed

[8] Hinks A, et al. Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis. Nat. Genet. 2013;45:664–669. - PMC - PubMed

[9] Liu JZ, et al. Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis. Nat. Genet. 2012;44:1137–1141. - PMC - PubMed

[10] Liu JZ, et al. Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis. Nat. Genet. 2012;44:1137–1141. - PMC - PubMed

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Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

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Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

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